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Other titles in the Signals and Communication Technology series:

Foundations and Applications of Sensor Management (Signals and Communication Technology)

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Foundations and Applications of Sensor Management (Signals and Communication Technology) Cover

 

Synopses & Reviews

Publisher Comments:

Over the past few years the problem of active sensing has received an increasing amount of attention from researchers in areas such as signal processing, automatic control, statistics, and machine learning. Active sensing is recognized as an enabling technology for the next generation of agile, multi-modal, and multi-waveform sensor platforms to efficiently perform tasks such as target detection, tracking, and identification. In active sensing, the sequence of sensor actions, such as pointing angle, modality, or waveform, are selected adaptively based on information extracted from past measurements. When the adaptive selection rule is carefully designed such an on-line active approach to sensing can very significantly improve overall performance as compared to off-line approaches. However, due to the classic curse of dimensionality, design and implementation of optimal active sensing strategies has been and remain very challenging. Recently, several research programs at DARPA (SWARMS, ISP), ARO (MURI), and AFOSR (ATR MURI) have funded efforts in areas related to active sensing. These resulted in focused efforts by several research groups in academia, government laboratories, and industry. These efforts have led to advances in theory and implementation that have borne some fruit in specific technology areas. For example, several promising new methods to approximate optimal multistage sensor management strategies for target tracking have been developed and an understanding of design challenges and performance tradeoffs is beginning to emerge. This book introduces the area, takes stock of these advances, and describes open problems and challenges in order to advance the field.

Synopsis:

<P>Sensor management is an enabling technology for the next generation of agile, multi-modal, and multi-waveform sensor platforms to efficiently perform tasks such as target detection, tracking, and identification. In sensor management the sequence of sensor actions, such as pointing angle, modality, or waveform, are selected adaptively based on information extracted from past measurements. This book presents the theory of sensor management with applications to real world examples such as adaptive mine detection, adaptive signal and image sampling, multiple target tracking, and radar waveform design. It is written by leading experts in the field for a diverse engineering audience ranging from signal processing, to automatic control, mathematical statistics, and machine learning. The level of treatment of the book is tutorial and self contained. The chapters of the book are grouped into three sections: theoretical foundations; approximate approaches; and applications. The book assumes the reader has a technical background at the level of a first year graduate student in one of the systems engineering disciplines, e.g. signal processing, control, or communications. An appendix is included on topics that the reader may not have seen as a first year graduate student such as: partially observable markov processes, statistical decision theory, information theory, and dynamic programming.</P>

Synopsis:

This book covers control theory signal processing and relevant applications in a unified manner. It introduces the area, takes stock of advances, and describes open problems and challenges in order to advance the field. The editors and contributors to this book are pioneers in the area of active sensing and sensor management, and represent the diverse communities that are targeted.

Synopsis:

Foundations and Applications of Sensor Management presents the emerging theory of sensor management with applications to real-world examples such as landmine detection, adaptive signal and image sampling, multi-target tracking, and radar waveform scheduling. It is written by leading experts in the field for a diverse engineering audience ranging from signal processing, to automatic control, statistics, and machine learning. The level of treatment of the book is tutorial and self-contained. The chapters of the book follow a logical development from theoretical foundations to approximate approaches and ending with applications. The coverage includes the following topics: stochastic control foundations of sensor management; multi-armed bandits and their connections to sensor management; information-theoretic approaches; managed sensing for multi-target tracking; approximation methods based on embedded simulation; active learning for classification and sampling; and waveform scheduling for radar. An appendix is included to provide essential background on topics the reader may not have encountered as a first-year graduate student: Markov decision processes; information theory; and stopping times. Foundations and Applications of Sensor Management is an important reference for signal processing and control engineers and researchers as well as machine learning application developers.

Table of Contents

Overview of Book.- Stochastic Control Theory for Sensor Management.- Information Theoretic Approaches to Sensor Management.- Joint Multi-Target Particle Filtering.- POMDP Approximation Using Simulation and Heuristics.- Multi-Armed Bandit Problems.- Application of Multi-Armed Bandits to Sensor Management.- Active Learning and Sampling.- Plan-in-Advance Learning.- Sensor Scheduling in Radar.- Defense Applications.

Product Details

ISBN:
9780387278926
Author:
Hero, Alfred Olivier
Publisher:
Springer
Editor:
Kastella, Keith
Editor:
Castanon, David
Editor:
Cochran, Doug
Author:
Casta"n, David
Author:
Kastella, Keith
Author:
Castanon, David
Author:
Cochran, Doug
Subject:
Engineering - Electrical & Electronic
Subject:
Automation
Subject:
Electronics - Microelectronics
Subject:
Electricity
Subject:
Engineering / Electrical
Subject:
Casta"n
Subject:
Cochran
Subject:
Hero
Subject:
Kalman filtering.
Subject:
Kastella
Subject:
active sensing
Subject:
automatic controls
Subject:
Machine learning
Subject:
target detection
Subject:
tracking identification
Subject:
waveform sensor
Subject:
Signal, Image and Speech Processing
Subject:
Control, Robotics, Mechatronics
Subject:
Coding and Information Theory
Subject:
Communications Engineering, Networks
Subject:
Electrical engineering
Subject:
Electrical Engineering <P>Active sensing is recognized as an enabling technology for the next generation of agile, multi-modal, and multi-waveform sensor platforms to efficiently perform tasks such as target detection, tracking, and identification. Recent
Subject:
Electricity-General Electricity
Subject:
Electronics - General
Copyright:
Edition Description:
Book
Series:
Signals and Communication Technology
Publication Date:
20071115
Binding:
HARDCOVER
Language:
English
Illustrations:
Y
Pages:
328
Dimensions:
235 x 155 mm

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Related Subjects

Children's » General
Computers and Internet » Computer Architecture » Signal Processing
Engineering » Communications » Telephony
Reference » Science Reference » Technology
Science and Mathematics » Electricity » General Electricity
Science and Mathematics » Electricity » General Electronics

Foundations and Applications of Sensor Management (Signals and Communication Technology) New Hardcover
0 stars - 0 reviews
$219.75 In Stock
Product details 328 pages Springer - English 9780387278926 Reviews:
"Synopsis" by , <P>Sensor management is an enabling technology for the next generation of agile, multi-modal, and multi-waveform sensor platforms to efficiently perform tasks such as target detection, tracking, and identification. In sensor management the sequence of sensor actions, such as pointing angle, modality, or waveform, are selected adaptively based on information extracted from past measurements. This book presents the theory of sensor management with applications to real world examples such as adaptive mine detection, adaptive signal and image sampling, multiple target tracking, and radar waveform design. It is written by leading experts in the field for a diverse engineering audience ranging from signal processing, to automatic control, mathematical statistics, and machine learning. The level of treatment of the book is tutorial and self contained. The chapters of the book are grouped into three sections: theoretical foundations; approximate approaches; and applications. The book assumes the reader has a technical background at the level of a first year graduate student in one of the systems engineering disciplines, e.g. signal processing, control, or communications. An appendix is included on topics that the reader may not have seen as a first year graduate student such as: partially observable markov processes, statistical decision theory, information theory, and dynamic programming.</P>
"Synopsis" by , This book covers control theory signal processing and relevant applications in a unified manner. It introduces the area, takes stock of advances, and describes open problems and challenges in order to advance the field. The editors and contributors to this book are pioneers in the area of active sensing and sensor management, and represent the diverse communities that are targeted.
"Synopsis" by , Foundations and Applications of Sensor Management presents the emerging theory of sensor management with applications to real-world examples such as landmine detection, adaptive signal and image sampling, multi-target tracking, and radar waveform scheduling. It is written by leading experts in the field for a diverse engineering audience ranging from signal processing, to automatic control, statistics, and machine learning. The level of treatment of the book is tutorial and self-contained. The chapters of the book follow a logical development from theoretical foundations to approximate approaches and ending with applications. The coverage includes the following topics: stochastic control foundations of sensor management; multi-armed bandits and their connections to sensor management; information-theoretic approaches; managed sensing for multi-target tracking; approximation methods based on embedded simulation; active learning for classification and sampling; and waveform scheduling for radar. An appendix is included to provide essential background on topics the reader may not have encountered as a first-year graduate student: Markov decision processes; information theory; and stopping times. Foundations and Applications of Sensor Management is an important reference for signal processing and control engineers and researchers as well as machine learning application developers.
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